78 citations · 117 across the 7 of their papers we have counts for
8 papers
Trainable Smooth-Rotation Transforms with Learned Channel Scales for LLM Quantization
Patrik Czakó, Gábor Kertész, Sándor Szénási
Post-training quantization (PTQ) is one of the most practical ways to reduce the serving cost of Large Language Models (LLMs), but activation quantization remains difficult because…
Object Counting with GPT-4o and GPT-5: A Comparative Study
Richard Füzesséry, Kaziwa Saleh, Sándor Szénási +1
Zero-shot object counting attempts to estimate the number of object instances belonging to novel categories that the vision model performing the counting has never encountered duri…
GPT-4 for Occlusion Order Recovery
Kaziwa Saleh, Zhyar Rzgar K Rostam, Sándor Szénási +1
Occlusion remains a significant challenge for current vision models to robustly interpret complex and dense real-world images and scenes. To address this limitation and to enable a…
SmoothRot: Combining Channel-Wise Scaling and Rotation for Quantization-Friendly LLMs
Patrik Czakó, Gábor Kertész, Sándor Szénási
We present SmoothRot, a novel post-training quantization technique to enhance the efficiency of 4-bit quantization in Large Language Models (LLMs). SmoothRot addresses the critical…
Turning LLM Activations Quantization-Friendly
Patrik Czakó, Gábor Kertész, Sándor Szénási
Quantization effectively reduces the serving costs of Large Language Models (LLMs) by speeding up data movement through compressed parameters and enabling faster operations via int…
Achieving Peak Performance for Large Language Models: A Systematic Review
Zhyar Rzgar K Rostam, Sándor Szénási, Gábor Kertész
In recent years, large language models (LLMs) have achieved remarkable success in natural language processing (NLP). LLMs require an extreme amount of parameters to attain high per…
Mask Guided Gated Convolution for Amodal Content Completion
Kaziwa Saleh, Sándor Szénási, Zoltán Vámossy
We present a model to reconstruct partially visible objects. The model takes a mask as an input, which we call weighted mask. The mask is utilized by gated convolutions to assign m…
Occlusion Handling in Generic Object Detection: A Review
Kaziwa Saleh, Sándor Szénási, Zoltán Vámossy
The significant power of deep learning networks has led to enormous development in object detection. Over the last few years, object detector frameworks have achieved tremendous su…